Die Messung des digitalen Reifegrads

Im Zuge der COVID-19 Pandemie, des verstärkten Kostendrucks, des Fachkräftemangels und der behördlichen Massnahmen hat die Digitalisierung die Schweizer Gesundheitsorganisationen voll erfasst. Dies betrifft nicht nur die medizinisch-pflegerischen Bereiche, sondern auch die nicht-medizinischen Supportprozesse. Gerade hier fehlen geeignete Instrumente, um die Gesundheitsorganisationen in ihrem Digitalisierungsprozess zu unterstützen. Abhilfe könnte die digitale Assessment Plattform schaffen, entstanden aus dem Forschungsprojekt Digital Competence for Healthcare DC4HC

Reifegradmodelle als Grundlage für den digitalen Veränderungsprozess im Facility Management in Healthcare : eine integrative Literaturrecherche

Healthcare organizations frequently lack the knowledge about the digital maturity of their non-medical support services to which facility management (FM) belongs. However, there is a significant leveraging effect in the digital transformation. It would be important for FM organizations to understanding their current digital capabilities in order to draw strategic decisions. Despite the extensive variety of maturity models, a comprehensive framework for this domain is lacking. The aim of this paper is to create a fundamental understanding, from which to develop a dedicated model. An integrative review was performed to systematically collect, screen and review the literature. A total of 124 articles were screened. Of these, 96 articles were further reviewed. The findings show that none of the identified maturity models cover all organizational domains and systems of healthcare organizations. Moreover, there is a clear contrast observed with digital maturity models in the FM domain. These maturity models mostly address individual technology applications, which limits the effectiveness of such models for an FM organization. Overall, the integrative review demonstrates the need to develop a holistic maturity model for FM in healthcare, that includes transformational capabilities, rather than just technological applications. As such a maturity model should offer a level of adaptability for healthcare organizations to align the model to their organizational characteristics

Artificial intelligence and machine learning for maturity evaluation and model validation

In this paper, we discuss the possibility of using machine learning (ML) to specify and validate maturity models, in particular maturity models related to the assessment of digital capabilities of an organization. Over the last decade, a rather large number of maturity models have been suggested for different aspects (such as type of technology or considered processes) and in relation to different industries. Usually, these models are based on a number of assumptions such as the data used for the assessment, the mathematical formulation of the model and various parameters such as weights or importance indicators. Empirical evidence for such assumptions is usually lacking. We investigate the potential of using data from assessments over time and for similar institutions for the ML of respective models. Related concepts are worked out in some details and for some types of maturity assessment models, a possible application of the concept is discussed

Transformation Compass für nicht-medizinische Supportprozesse (DE)

Im Rahmen des Innosuisse-Forschungsprojekt DC4HC wurde der Transformation Compass von Graf et al. (2019) erweitert und für die nicht-medizinischen Supportprozesse angepasst. Siehe: Graf, M., Peter, M. and Gatziu-Grivas, S. (2019), “Foster Strategic Orientation in the Digital Age”, in Abramowicz, W. and Paschke, A. (Eds.), Business Information Systems Workshops, Lecture Notes in Business Information Processing, Vol. 339, Springer International Publishing, Cham, pp. 420–432

Asynchronous Messaging for OSGi

OSGi is a popular Java-based platform, which has its roots in the area of embedded systems. However, nowadays it is used more and more in enterprise systems. To fit this new application area, OSGi has recently been extended with the Remote Services specification. This specification enables distribution, which OSGi was previously lacking. However, the specification provides means for synchronous communication only and leaves out asynchronous communication. As an attempt to fill a gap in this field, we propose, implement and evaluate an approach for the integration of asynchronous messaging into OSGi